Using Game Theory to Battle Wild Fires
Wildfires have become all too common in the United States. Being from California myself, I have witnesses wildfires become an anual concern as they consistently cause enormous damage to my neighboring communities.
This year, California has witnessed especially devastating wildfires. This season alone, almost 4 million acres have been burnt in the state, 96,000 residents have been evacuated, and and 30 lives have been lost with little hope in sight. With only 6% of the current fire outbreak contained, this fight with fires is far from over. It was while reading these devastating statistics in the news this morning that I realized I wanted to investigate the connection between wildfires and networks.
As I started my research, I fell upon a study which peaked my interested with its correlation to a major topic of the course: game theory. A 2013 study by the University of Waterloo described how different fire agencies interact when an agency is overloaded. The study’s discussion of the competitive nature around the limited fire-battling resources made me want to draw out a payoff matrix representing the dilemma agencies are faced with when fighting fires.
Although the study didn’t include a matrix, it did provide a rationale for potential payoffs which helped me craft my own matrix displayed above. For example, it was explained that a non distressed agency would feel social responsible to help a distressed one. Specifically, the article mentions how “social goodwill” incentivizes the agencies to aid each other, ultimately giving the agency that shares its resources a positive payoff. Of course, this concept wouldn’t apply to a distressed agency which gravely needs to reserve its resources. When the non distressed agency receives resources from the distressed agency, the additional resources have no result on its payoff, as the resources pose no value to a stable agency. On the other hand, the distressed agency is at a major loss as it gave away its much needed resources. Ultimately, when looking at the payoff matrix based off the study, we observe that both agencies have a dominant strategy. For the distressed agency, no sharing its resources will result in better payouts all around. Alternatively, the non distressed agency has a dominant strategy of sharing its resources and aiding the agency in need. Furthermore, the pure Nash equilibrium sits in the bottom left square, where the best outcome for both agencies occurs when they share resources to the one in need, and reserve their resources when under pressure. In conclusion, game theory helps give us insight on how fire agencies interact in a mutually beneficial manner while under pressure from fires and explains the enormously collaborative nature of the industry .
All in all, I found this application of game theory to be interesting in its application to a real world issue which involves solving problems. In its traditional applications, game theory includes two players going head to head, trying to win to a near malicious extent. However, this application demonstrates how game theory can be present in almost any competition, even when the two ‘players’ have a common goal.
Sources:
https://www.npr.org/2020/10/02/919554698/california-wildfires-near-tragic-milestone-4-million-acres-burned
https://cs.uwaterloo.ca/research/tr/2012/CS-2012-11.pdf